Proximie is on a mission to improve healthcare by transforming the world’s operating rooms into connected ecosystems of people, devices, and data.
Our Intelligence Suite transforms operating room (OR) performance, keeping teams in sync and workflows on track to maximise throughput. Simultaneously our computer vision and AI capabilities capture real-time data and detect surgical events – improving quality of data outputs. The result: ORs are optimised like never before – with predictive analytics and automated notifications ensuring patients and staff are in the right place at the right time.
Once practitioners are in the OR, our Surgical Suite enables real-time remote access and creates a secure video record of every procedure; improving training, education, and collaboration. It is an intuitive asset which helps instil a culture of continuous learning, accelerates the adoption of cutting-edge medical devices, and enhances surgical performance across the entire global workforce – improving outcomes and saving lives.
Proximie was commercialised in 2019 and is available in over 500 facilities globally.
Check out our Founder and CEO Nadine’s Origins Story here: https://www.proximie.com/about-us/
Position OverviewAs Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drives better insights and decision making, you will be the engineer who makes that intelligence dependable at scale. Using your deep technical expertise and real-world production experience, you will own the platform and the infrastructure that carry our machine learning solutions out of development and into hundreds of live hospitals, and keep them performing once they are there.
Our machine learning engineers own the models. You own everything that gets those models in front of a customer and keeps them running: the training and deployment infrastructure on AWS and SageMaker, reproducible and configuration-driven training runs, environments defined in code, release pipelines that make a deployment routine rather than an event, and the monitoring that tells us when a model's behaviour shifts in a theatre on the other side of the world. You will make the difference between a solution that works and a solution a hospital can depend on.
This is a commercial team, and the work is grounded in real operational problems rather than internal roadmaps. The role demands precision, judgement and a deep understanding of how machine learning behaves in production, at scale, in environments that do not forgive downtime. If you are excited by complex problems with life-changing impact and want to build the systems that get technology like this into the most critical environments in healthcare, we would love to hear from you.
Job Responsibilities
RequirementsEssential
Desirable* Event-driven and streaming architectures on AWS: Step Functions, Lambda, Kinesis, ECS, DynamoDB. * Model monitoring in production: inference logging and drift detection. * Exposure to healthcare, medical devices or another regulated industry.
Why Work for Proximie?
Proximie is an equal opportunity employer. We are committed to providing a work environment that supports, inspires, and respects all individuals. We do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under the law.
